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Unit outline_

FMBA5008: Data Analytics and Modelling

Semester 1b, 2026 [Block mode] - Castlereagh St, Sydney

This unit aims to develop the ability to effectively analyse and draw useful inferences from data in order to communicate complex interrelationships to senior management in a way that can lead to favourable and sustainable change. Topics covered include analysis of key macroeconomic variables and statistical concepts, demand modelling, performance measurement and benchmarking analysis, and quantifying the economics and financial risks. This unit provides students with an opportunity to work with real-world data sets and case studies, and to apply those data sets to various organisations

Unit details and rules

Academic unit Management Education
Credit points 6
Prerequisites
? 
None
Corequisites
? 
None
Prohibitions
? 
SMBA6003
Assumed knowledge
? 

None

Available to study abroad and exchange students

No

Teaching staff

Coordinator John-Paul Monck, john-paul.monck@sydney.edu.au
The census date for this unit availability is 1 May 2026
Type Description Weight Due Length Use of AI
Data analysis Individual Assignment
Report
40% Week 05
Due date: 10 May 2025 at 23:59

Closing date: 20 May 2025
1500 words AI allowed
Outcomes assessed: LO1 LO2 LO3 LO4
Presentation group assignment Group assignment
Presentation
40% Week 06
Due date: 18 May 2025 at 09:00

Closing date: 28 May 2025
3 slides per member AI allowed
Outcomes assessed: LO1 LO2 LO3 LO4
In-person written or creative task In-class test
Two part-long form
20% Week 07
Due date: 30 May 2025 at 10:00

Closing date: 30 May 2025
2 hours AI prohibited
Outcomes assessed: LO2 LO3 LO4
group assignment = group assignment ?

Assessment summary

  • Individual assignment including sustainability component: Students will write a professional report explaining how data analysis can be used to address a long-term issue of sustainable development within the Australian economy or another economy of your choice.
  • Group assignment: In groups of 5-6, students will prepare a powerpoint presentation discussing the key demand side risks associated with the venture with a focus on the macroeconomic performance of the target country.
  • In-class test: The final test will cover all the topics of the unit.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range

Description

High distinction

85 - 100

Awarded when you demonstrate the learning outcomes for the unit at an exceptional standard, as defined by grade descriptors or exemplars outlined by your faculty or school. 

Distinction

75 - 84

Awarded when you demonstrate the learning outcomes for the unit at a very high standard, as defined by grade descriptors or exemplars outlined by your faculty or school.

Credit

65 - 74

Awarded when you demonstrate the learning outcomes for the unit at a good standard, as defined by grade descriptors or exemplars outlined by your faculty or school.

Pass

50 - 64

Awarded when you demonstrate the learning outcomes for the unit at an acceptable standard, as defined by grade descriptors or exemplars outlined by your faculty or school. 

Fail

0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

According to University and Business School policies.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students,  includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

WK Topic Learning activity Learning outcomes
Week 01 Economic Overview Lecture (7 hr) LO2 LO3 LO4
Basic Data Analytics Skills Lecture (7 hr) LO1 LO2
Week 03 Economic Linkages Lecture (7 hr) LO1 LO2 LO4
Modelling - Introduction Lecture (7 hr) LO1 LO2 LO3
Week 04 (1) Modelling - Working with Complex Data (2) Modelling - Exercise Lecture (7 hr) LO1 LO2
Economic Levers Lecture (7 hr) LO1 LO2 LO3
Week 05 Data Mining for Business Lecture (7 hr) LO1 LO2 LO4
(1) Risk Management (2) Scenario Analysis Lecture (7 hr) LO2 LO3 LO4
Week 06 Assessment Assessment (7 hr) LO1 LO2 LO3 LO4

Attendance and class requirements

Lecture recordings and attendance: Note that MBA classes held at the CBD Campus are not systematically recorded and 100% class attendance is expected for each unit of the MBA Program. If there are extenuating circumstances as to why you are not able to attend a particular class, please contact your unit coordinator as soon as possible, and also notify your group members (if the unit has a group work component).

¸ßÇ帣ÀûƬ commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. Develop evidence-based business recommendations to solve complex problems, drawing on appropriate data (including economic considerations), analytical techniques and ethical and sustainability considerations
  • LO2. Predict the impact of external factors emanating from the world economy on the company’s performance using appropriate data-driven modelling techniques.
  • LO3. Communicate complex ideas to senior management using appropriate communication styles and evidence-based recommendations.
  • LO4. Collaborate with colleagues and peers to solve complex data-related problems using innovative tools and solutions while arriving at a consensus among peers.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

This section outlines changes made to this unit following staff and student reviews.

No changes have been made since this unit was last offered.

Disclaimer

Important: the University of Sydney regularly reviews units of study and reserves the right to change the units of study available annually. To stay up to date on available study options, including unit of study details and availability, refer to the relevant handbook.

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